activity
20132023
most citedElliptical graphical modelling

52 citations · 91 across the 11 of their papers we have counts for

collaborators

14 papers

stat.ME2023

Models for temporal clustering of extreme events with applications to mid-latitude winter cyclones

Christina Mathieu, Merle Mendel, Katharina Hees +1

The occurrence of extreme events like heavy precipitation or storms at a certain location often shows a clustering behaviour and is thus not described well by a Poisson process. We…

stat.ME2023

Intervention analysis for integer-valued autoregressive models

Xanthi Pedeli, Roland Fried

We study the problem of intervention effects generating various types of outliers in an integer-valued autoregressive model with Poisson innovations. We concentrate on outliers whi…

math.ST2020

An Asymptotic Test for Constancy of the Variance under Short-Range Dependence

Sara Kristin Schmidt, Max Wornowizki, Roland Fried +1

We present a novel approach to test for heteroscedasticity of a non-stationary time series that is based on Gini's mean difference of logarithmic local sample variances. In order t…

math.ST2019

QANOVA: Quantile-based Permutation Methods For General Factorial Designs

Marc Ditzhaus, Roland Fried, Markus Pauly

Population means and standard deviations are the most common estimands to quantify effects in factorial layouts. In fact, most statistical procedures in such designs are built towa…

math.ST2019★ 1 cited

Robust change point tests by bounded transformations

Alexander Dürre, Roland Fried

Classical moment based change point tests like the cusum test are very powerful in case of Gaussian time series with one change point but behave poorly under heavy tailed distribut…

stat.ME2017

Dealing with seasonal variability and inter-site dependence in regional flood frequency analysis

Paul Kinsvater, Friederike Deiters, Roland Fried

This paper considers the regional estimation of high quantiles of annual maximal river flow distributions , an important problem from flood frequency analysis. Even though this…